Computer simulation of the human brain at an individual neuron resolution is an ultimate goal of computational neuroscience. The Japanese flagship supercomputer, K, provides unprecedented computational capability toward this goal. The cerebellum contains 80% of the neurons in the whole brain. Therefore, computer simulation of the human-scale cerebellum will be a challenge for modern supercomputers. In this study, we built a human-scale spiking network model of the cerebellum, composed of 68 billion spiking neurons, on the K computer. As a benchmark, we performed a computer simulation of a cerebellum-dependent eye movement task known as the optokinetic response. We succeeded in reproducing plausible neuronal activity patterns that are observed experimentally in animals. The model was built on dedicated neural network simulation software called MONET (Millefeuille-like Organization NEural neTwork), which calculates layered sheet types of neural networks with parallelization by tile partitioning. To examine the scalability of the MONET simulator, we repeatedly performed simulations while changing the number of compute nodes from 1,024 to 82,944 and measured the computational time. We observed a good weak-scaling property for our cerebellar network model. Using all 82,944 nodes, we succeeded in simulating a human-scale cerebellum for the first time, although the simulation was 578 times slower than the wall clock time. These results suggest that the K computer is already capable of creating a simulation of a human-scale cerebellar model with the aid of the MONET simulator.

中文翻译：

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在 K Computer 上模拟人体规模的小脑网络模型

以单个神经元分辨率对人脑进行计算机模拟是计算神经科学的最终目标。日本旗舰超级计算机 K 为实现这一目标提供了前所未有的计算能力。小脑含有全脑80%的神经元。因此，人体小脑的计算机模拟将是现代超级计算机面临的挑战。在这项研究中，我们在 K 计算机上构建了一个人体规模的小脑尖峰网络模型，该模型由 680 亿个尖峰神经元组成。作为基准，我们对小脑依赖性眼球运动任务（称为视动反应）进行了计算机模拟。我们成功地再现了在动物实验中观察到的合理的神经元活动模式。该模型建立在名为 MONET（类 Millefeuille 组织神经网络）的专用神经网络仿真软件上，该软件通过平铺分区并行计算神经网络的分层片类型。为了检查 MONET 模拟器的可扩展性，我们将计算节点数量从 1,024 个更改为 82,944 个，反复进行模拟，并测量计算时间。我们观察到我们的小脑网络模型具有良好的弱缩放特性。使用全部 82,944 个节点，我们首次成功模拟了人类规模的小脑，尽管模拟速度比挂钟时间慢了 578 倍。这些结果表明，K 计算机已经能够在 MONET 模拟器的帮助下创建人体规模的小脑模型的模拟。